计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 142-146.doi: 10.11896/jsjkx.201200071

• 智能计算 • 上一篇    下一篇

基于高斯-柯西变异的帝国竞争算法优化

魏昕, 冯锋   

  1. 宁夏大学信息工程学院 银川750021
  • 出版日期:2021-11-10 发布日期:2021-11-12
  • 通讯作者: 冯锋(feng_f@nxu.edu.cn)
  • 作者简介:963314941@qq.com
  • 基金资助:
    宁夏重点研发计划重点项目(2018BFG02003);宁夏大学研究生创新项目(GIP2020091)

Optimization of Empire Competition Algorithm Based on Gauss-Cauchy Mutation

WEI Xin, FENG Feng   

  1. School of Information Engeineering,Ningxia University,Yinchuan 750021,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:WEI Xin,born in 1996,postgraduate.His main research interests include improvement of intelligent algorithm.
    FENG Feng,born in 1971,Ph.D,professor.His main research interests include information system engineering and application and so on.
  • Supported by:
    Major Projects of Ningxia Key Research and Development Plan(2018BFG02003) and Postgraduate Innovation Project of Ningxia University(GIP2020091).

摘要: 为解决帝国竞争算法(Imperial Competitive Algorithm,ICA)竞争过程中收敛速度慢和易陷入局部最优的问题,提出了一种基于高斯-柯西变异的帝国竞争算法(Imperial Competitive Algorithm Based on Gauss-Cauchy Mutation,GCICA)。在ICA帝国竞争时引入高斯变异,加快竞争过程中的收敛速度;帝国灭亡后多样性减少且仅在小范围区域内进行寻优,引入柯西变异,使其跳出局部最优。分析引入高斯、柯西、高斯-柯西变异后的算法在多个典型基准测试函数上的仿真结果,GCICA的收敛速度和寻优精度都得到了提升。

关键词: 帝国竞争算法, 高斯变异, 柯西变异, 优化算法

Abstract: In order to solve the problems of slow convergence speed and easy to fall into local optimum in the competition process of imperial competitive algorithm (ICA),a new imperial competitive algorithm based on Gauss-Cauchy mutation (GCICA) is proposed.Gauss mutation is introduced in ICA Empire competition to speed up the convergence speed in the competition process;after the Empire perishes,the diversity is reduced and only in a small area for optimization,and Cauchy mutation is introduced to make it jump out of local optimum.By analyzing the simulation results of the algorithm with Gauss,Cauchy and Gauss-Cauchy mutation on several typical benchmark functions,the convergence speed and optimization accuracy of GCICA are improved.

Key words: Cauchy mutation, Gauss mutation, Imperial competition algorithm, Optimization algorithm

中图分类号: 

  • TP301.6
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